No abstract

Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively.

Land surface albedo is a critical variable in determining surface energy balance, and regulating climate and ecosystem processes through feedback mechanisms. Therefore, climatic modelers and radiative monitoring require accurate estimates of land surface albedo. With the instrument development, algorithm upgrade, spectral-band-adjustment in wavelength center or band width, and the increasing distinct requirement from diversified communities, various albedo terms have been generated in related satellite-based products. The lack of understanding on the divergence of these terminologies can introduce potential considerable errors in the subsequent applications, or an elevated probability to invert the deduced conclusion. We surveyed the basic concepts of reflectance quantities, retrieval strategies, and models developed since the 1970s, and discuss both strength and opportunity for improvements on land surface albedo extraction, and product generation. In addition, we exemplified the difference of albedo terms using the daily MODIS product (MCD43A) to emphasize the potential risk of the ambiguous usage, over typical IGBP land covers in Northern Kazakhstan. Our investigation shows that relative differences among various albedo terms can reach up to 181% and 50%, while 0.266 and 0.118 of absolute variance respectively in the narrow and broad-band surface albedo, which illuminated cautions against the ambiguous understanding of albedo terminologies or erroneous usage of albedo products.